smu mk0017-slm-unit-05

e-Marketing Unit 5

Sikkim Manipal University Page No. 84

Unit 5 e-Marketing Data Collection and Handling

Structure:

5.1 Introduction

Objectives

5.2 Types of Data in e-Marketing

User Entry Data / Profiles

Web Documents and Web Meta Data

Server and Cookie Data

5.3 Knowledge Management for e-Marketing

5.4 Marketing Information Systems for e-Marketing

5.5 Marketing Intelligence Systems

5.6 Managing Database Systems

Data Warehouse

Data Mining

5.7 Online Experimental Research and Survey

5.8 Web Analytics

Web Server Log File Analysis

Page Tagging

5.9 Knowledge Management Metrics

5.10 Summary

5.11 Glossary

5.12 Terminal Questions

5.13 Answers

5.14 Case-let

5.1 Introduction

After studying the previous units you must be familiar with the plans and

strategies adopted in e-marketing and how it they are implemented.

This unit takes you to the next step and helps you to understand how to

manage information in e-marketing, the types of data that are available, the

intelligence systems and information systems for e-marketing and also

database systems, which include data ware house and data mining. It also

explains the knowledge management metrics, Web analytics and online

experimental research and survey.

e-Marketing Unit 5


Objectives:

After studying this unit, you should be able to:

list the types of data applicable in e-marketing

explain knowledge management, information and intelligence systems

describe various data base systems

analyse online experiments research and survey

explain the role of web analytics

evaluate knowledge management metrics

5.2 Types of Data in e-Marketing

Let us see the types of data used in e-marketing, which are discussed here -

5.2.1 User Entry Data / Profiles

Gathering of data from visitors over a website on online forms is a very

popular way of getting user information. Usually the website visitor has to fill

in into these forms information like name, address, contact number, lifestyle

information and user interests so on.

This information, which is directly stored into a data base, is used later for

data mining. However, for a user, it is often tedious and time consuming to

answer all these questions. Therefore, on-line forms and questionnaires

should be created in such a way that they do not take much of the user‟s

time and that the user is motivated to give all the required answers.

5.2.2 Web Documents and Web Meta Data

Web documents Hypertext Mark-up Language (HTML) contain information

such as text, images, video or audio, which allow the users to recognise the

title of the page, keywords, the author and the main body.

Web metadata gives us the topology of a website, which is generally stored

as a side-specific index table implemented as a directed graph. These meta

data needs to be manually specified by the website administrator, which

becomes a very difficult job when it comes to large websites. Hence,

methods to annotate these documents automatically have been developed

in the recent past.

5.2.3 Server and Cookie Data

The server automatically generates the web server logs when a user visits a

Uniform Resource Locator URL. The server registers the Internet Protocol

e-Marketing Unit 5


(IP) address of the visitor, the time at which the user entered the website,

the time duration of the visit, the requested URL and the URL visited. From

this information, the path where the user is going on the website can be

generated. Web server logs provide important information that can help to

determine the behaviour of the user at the website. However, the IP address

stored in the server log does not always lead to the particular user, since the

address might have been changed by the proxy server. Therefore, cookie

logs might be more preferable.

Cookies are short text files that are generated by the server on the client site

while the client‟s browser is visiting the website. Cookies allow setting a

special identification number or a code for a particular user. This code helps

to identify the user each time the user visits the website. However, to set a

cookie one needs the permission of the user, which is not always the case.

Therefore, a combination of server logs and cookie log will serve to be a

good basis for data mining.

Activity 1

Search for the cookies file(s) on your hard drive, by using the find file

function on your Microsoft PC. Do you see sites that you have never

visited? Is Double Click on the list? If so, visit the Double Click site to see

why.

Self Assessment Questions

1. User entries could be taken as ___________.

2. ___________ contain information such as text, images, video or audio.

3. Short text files are called _____________.

4. A combination of _________ and ____________ will be a good basis

for data mining.

5.3 Knowledge Management for e-Marketing

Knowledge management is getting progressively critical for the success of

companies in this emerging era of e-marketing. As business activities

increasingly shift to the web, the challenge facing corporate management is

maintaining competitive advantage by building strong relations with

employees, customers, and upstream/downstream suppliers and partners.

This is where a good knowledge management strategy comes into picture.

e-Marketing Unit 5


Unfortunately, many companies use knowledge management technologies

that do not serve to solve the above challenge. Therefore, it is important to

understand and implement management programs that can help companies

to gain competitive advantage over others. However, most experts agree

that the biggest challenges of knowledge management are not technological

but human-based or behavioural challenges.

We will now see how companies can benefit by adopting strategies that

harness the potential of marketing knowledge management technologies to

transform their e-business activities.

First of all, let us know the definition of knowledge management and then try

to understand the driving and impeding forces that help and hinder proper

deployment of knowledge management strategies in e-marketing.

Why Knowledge Management?

70% of companies that participated in a research study said that their sales

growth strategy for the year will be focused on optimising the sales

progression. How would they do that? Allowing sales people to focus on

having conversations, rather than digging up the materials they need to

support the new relationships that they are building is one way of increasing

the efficiency. This is the area in which marketing and knowledge

management can assist.

Making sales is considered as a hard task. To be successful in sales, you‟ve

got to have a deep understanding of your products and services, keep track

of many relationships, understand market trends, and withstand a significant

amount of pressure. Added to this, many departments will be constantly

trying to interface directly with you, which can lead to an overwhelming

number of mixed messages. In response to this, salespeople often try to

cover up by selling the products that they are most comfortable with, which

is not necessarily good for the company or consistent with the larger

business strategy. Hence, a significant part of marketing comprises

empathising with the sales people (they are customers of marketing), and

trying to provide them with products and services that meet their needs and

make their lives better.

Knowledge management is one way to make the necessary preparations

quicker by keeping all the relevant assets in one place – for the use of the

e-Marketing Unit 5


sales team. But, knowledge management is not just about making the

content accessible, it‟s about putting it in context, and improving its quality. It

is less about creating content and more about taking the collective

knowledge of the organisation and preparing it as a resource for the

organisation.


5. _____________ has become progressively more critical for the

success of companies in this emerging era of e-marketing.

6. A good knowledge management strategy can help in achieving the

organisational ______________.

7. Knowledge management is one way to make the necessary planning

________________.

5.4 Marketing Information Systems for e-Marketing

A Marketing Information System can be defined as 'a system in which

marketing information is formally gathered, stored, analysed and distributed

to managers in accordance with their informational needs on a regular basis'

(Jobber, 2007)

The system is created based on an understanding of the information needs

of marketing management. A Marketing Information System supplies all the

information that a marketing manager needs. The data is collected from the

marketing environment and transferred into the information system.

Marketing managers can use this information in their decision-making

processes.

A marketing information system has four components: the internal reporting

system, the marketing research system, the marketing intelligence system

and marketing models. Internal reports include orders received, inventory

records and sales invoices. Marketing research is a purposeful study –

either ad hoc or continuous. However, marketing intelligence is less specific

in its purposes, and is chiefly carried out in an informal manner. It is carried

out by managers themselves rather than by professional marketing

researchers.

Let us check out this definition of MIS -

"A marketing information system is a continuing and interacting structure of

people, equipment and procedures to gather, sort, analyse, evaluate, and

e-Marketing Unit 5


distribute pertinent, timely and accurate information for use by marketing

decision makers to improve their marketing planning, implementation, and

control".

The main purpose of a Marketing Information System is to support

management decision making. You must be aware of the five distinct

functions of management – planning, organising, coordinating, decision

making and controlling. Each of these functions is supported by the MIS.

Figure 5.1 illustrates the major components of an MIS, the environmental

factors monitored by the system and the types of marketing decisions which

the MIS seeks to underpin.

As you can see in Figure 5.1, this model of MIS begins with a description of

each of its four main constituent parts: the internal reporting systems, the

marketing research system, the marketing intelligence system and the

marketing models. Though an MIS varies in its degree of sophistication due

to the fact that all the countries in the world are not extensively

computerised, it is recommended that a fully-fledged MIS has all the above

components.

Marketing

Environment

Markets

channels

competitors

Political

Legal

Economy

Technology

Internal Report

System

Marketing

Research System

Marketing

Intelligence

Systems

Marketing

Models

Strategic

Decisions

Control

Decisions

Operational

Decisions

Data

Marketing decision and communications

Information

Figure 5.1: The Marketing Information System and its Subsystems

e-Marketing Unit 5


Information systems have to be designed to meet the way in which

managers tend to work. Research suggests that a manager continually

addresses a large variety of tasks and is able to spend relatively brief

periods on each of these. Given the nature of the work, managers tend to

rely upon information that is timely and verbal (because this can be

assimilated quickly), even if this is likely to be less accurate than more

formal and complex information systems.

Managers need to continually address a large variety of tasks, and given the

time constraints, they end up spending relatively brief periods on each of

them. Based on the nature of the work, managers tend to rely upon

information that is timely, even if this is likely to be less accurate than more

formal and complex information systems. Hence an MIS should be created

in such a way that it meets the information needs of managers.

Managers play at least three separate roles: interpersonal, informational and

decisional. An MIS, in electronic form or otherwise, supports all the three

roles in varying degrees.

Decision making can be divided into three levels: strategic, control (or

tactical) and operational. Strategic decisions are typically one-off situations

that have implications for changing the structure of an organisation. Hence,

the MIS must provide information which is precise and accurate. Control

decisions deal with broad policy issues and operational decisions concern

the management of the organisation's marketing mix. An MIS has to support

all these three levels of decision making.

MIS in e-Marketing

In the past, marketers asked information technology or information systems

personnel what software they had on the shelf. Today, however,

e-marketing actually drives technology change. E-marketing has changed

the MIS landscape in several ways. First, many firms store electronic

marketing data in databases and data warehouses. These data warehouses

enable marketers to obtain valuable, appropriate, and tailored information –

day or night. Second, marketers can receive database information in Web

pages and e-mail on a number of appliances in addition to the desktop

computer: pagers, fax machines, PDAs such as the Palm Treo and even

cellular phones. Third, customers also have access to portions of the

database. For example, when customers visit Amason.com, they can query

e-Marketing Unit 5


the product database for book titles and also receive information about their

account status and past book purchases. Customers, channel members,

and partners often have access to customer sales data to facilitate product

planning. Customer inquiries are usually automated, with personalised web

pages created instantaneously from customer databases. Most firms

recognise that data and information are useless, unless turned into

knowledge to increase profits. Therefore, cutting-edge firms make one

employee‟s project reports, proposals, and data analyses available to other

stakeholders in the MIS network.

The internet and other technologies greatly facilitate marketing data

collection. Internal records give marketing planners excellent insights about

sales and inventory movement. Secondary data helps marketers understand

competitors, consumers, the economic environment, political and legal

factors, technological forces, and other factors that affect an organisation.

Marketing planners use the internet, the telephone, product bar code

scanners, and other technologies to collect primary data about consumers.

Through online e-mail and Web surveys, online experiments, focus groups,

and observation of internet user discussions, marketers learn about both

current and prospective customers.


8. Following are the main MIS aspects once data is gathered EXCEPT -

a. Storing data c. Manipulating data

b. Distributing data d. Analysing data

9. _____________ enable marketers to obtain tailored information.

10. Marketing information systems are proposed to support management

________________.

5.5 Marketing Intelligence Systems

A Marketing Intelligence System is a set of procedures and practices

employed in analysing and assessing marketing information gathered

continually from sources inside and outside an organisation. The analysed

data provides the basis for decisions such as product development/

improvement, pricing, packaging, distribution, media selection and

promotion.

e-Marketing Unit 5


A Market Intelligence System that is customised to the size of your business

helps you fulfill customers' needs very well, because it identifies their

profiles, purchasing habits and motives and their wants and needs.

Marketing managers gather marketing intelligence by reading books,

newspapers, and trade publications, talking to customers, suppliers, and

distributors, monitoring "Social Media" on the internet via online discussion

groups, e-mailing lists and blogs and meeting with other company

managers.

Several steps to improve the quality of marketing intelligence:

Training and motivating the sales force to speck and report new

developments.

Motivating distributors, retailers, and other intermediates

External networking

Setting up a company advisory panel

Taking advantage of government data resources

Purchasing information from outside suppliers

Using online customer feedback systems to collect competitive

intelligence.


11. ____________ is gathered by reading books, newspapers, and trade

publications.

12. The quality of marketing intelligence is measured by ____________.

13. Use ____________ systems to collect competitive intelligence.

14. _____________ and _______________ the sales force makes them

collect and report new developments.

5.6 Managing Database Systems

Data collected from all customer touch points is stored in the data

warehouse knowledge management system, ready for analysis and

distribution to marketing decision makers.

Email programmes have address books with the capacity to store a variety

of information about each contact. In the initial stages of developing the list,

a company can use this capacity to build up information about contacts.

Using personalisation such as first names in emails increases response

rates.

e-Marketing Unit 5


As the list grows, the company needs to consider how the contact and

response details should be stored – this is where a database becomes

useful. A database provides the extra flexibility in storing and managing the

contact details. However, if the number of contacts is very small, a spread-

sheet can also be used to track the contact details.

If the company is trying to manage a large contact database over time, a

CRM system (client relationship management system) will prove very useful.

This will not only allow the organisation to keep track of its contacts, but also

to keep track of the interactions with them and to target them specifically

according to the groupings created by the organisation. Civi-CRM is one of

the Open Source CRMs worth investigating. Civil Mail, the mass-mailing

component for Civi-CRM allows a company to engage its constituents with

personalised emails and newsletters. It can also work alongside Internet

Content Management Systems like Drupal and Joomla.

With Civi Mail, an organisation can:

Target mailings by including or excluding any number of CiviCRM groups, or

previous mail recipients.

Personalise the messages using mail-merge tokens.

Track when recipients open the message.

Track click-through.

5.6.1 Data Warehouse

Date warehouses are repositories for the entire organisation‟s historical data

(not just marketing data). They are designed specifically to support analyses

necessary for decision-making. In other words, marketers cannot apply the

data in product or customer databases to marketing problems as well as

they can apply information in a data warehouse. Sometimes, the data in a

warehouse is separated into more specific subject areas (called data marts)

and indexed for easy use. These concepts are important for marketers

because they use data warehouse information for planning purposes.

5.6.2 Data Mining

It is the process of extracting patterns from data. Data mining is becoming

an increasingly vital tool to transform data into information. It is generally

used in a wide range of profiling practices such as marketing, surveillance,

fraud detection and scientific discovery.

e-Marketing Unit 5


Data mining can be used to reveal patterns in data, but is often carried out

only on samples of data. The mining process will not be effective if the

samples are not a good demonstration of the larger body of data. Data

mining cannot determine patterns that may be present in the larger body of

data if those patterns are not present in the sample being "mined". The

terms data dredging, data fishing and data snooping refer to the use of data

mining techniques to sample sizes that are very small for statistical

inferences to be made about the validity of any patterns discovered. You

can however, use data dredging to develop new hypothesis, which you must

validate with sufficiently large sample sets.

The following four classes of tasks are included in data mining:

Clustering - Clustering is the task of finding groups and structures in the

data that are in some way or the other “similar".

Classification – Classification is the task to generalise known structure to

apply to new data. For example, an email plan might attempt to classify an

email as genuine or spam. Common algorithms consist of decision tree

learning, nearest neighbour, naive Bayesian classification and neural

networks.

Regression – Regression attempts to find a task which models the data with

the least error.

Association rule learning – Association rule learning searches for

relationships between variables. For example, a supermarket might gather

data on customer purchasing practice. Using organisation rule learning, the

supermarket can determine which products are frequently bought together

and use this information for marketing purposes.


15. Data mining is a process for extracting patterns for data. (True/ False)

16. Regression is a type of _______________.

5.7 Online Experimental Research and Survey

Survey:1 It is a method of collecting information from a different number of

persons, known as a sample, in order to study something about the larger

population from which the sample is drawn. Even though surveys come in

1 www.activecampaign.com

e-Marketing Unit 5


many forms, some surveys concentrate on opinion and attitudes while

others are more concerned with collecting and gathering accurate

information.

Example: Many soap product companies conduct surveys to know where

exactly and how their product is running and how people feel about the

product. This is some times done on a door to door basis.

Experimental research is an efficient and scientific approach in which the

user or researcher manipulates controls and measures any change in the

variables. The input for the research is the survey findings.

The purpose of experimental research is to study the cause and effect

relationships.

An important characteristic of experimental research is active manipulation

of an independent variable. Here is an example of an experiment.

Table: 5.1: Experimental Data

Pre-test Treatment Post test

O1 XE O2

O1 XC O2

Where:

E stands for the experimental group (e.g., new teaching approach)

C stands for the control or comparison group (e.g., the old or standard

teaching approach)

The best way to make the two groups similar in the above research design

is to randomly assign the participants to the experimental and control

groups. Let‟s assume that we have a convenience sample of 50 people and

that we randomly assign them to the two groups in our experiment.

Here is the logic of this experiment. First, the groups are made

approximately the same at the start of the study by using a random

assignment (i.e., the groups are “equated”). Then, the participants are put

through pre-tests to see how much they know.

Using the new teaching approach with the experimental group and using the

old teaching approach for the control group, the independent variable is

manipulated.

e-Marketing Unit 5


After the manipulation, the participants‟ knowledge is measured to see how

much they know after having participated in the experiment. Let‟s assume

that the people in the experimental group show more knowledge

improvement than those in the control group. What would be the

conclusion? In this case, it can be concluded that there is a causal

relationship between the independent variable – teaching method and the

dependent variable – knowledge, and it can be specifically concluded that

the new teaching approach is better than the old teaching approach.

Here are some merits and demerits of online experimental research and

survey.

Table 5.2: Merits and Demerits of Online Experimental Research and Survey

Merits Demerits

Online research and survey is faster.

Targeting audience with online survey is difficult

Data-entry accuracy

The internet might slow down due to overload, which makes online exchange of information delayed.

High Security

A system might crash or hang, due to which purchasing or selling might be delayed

Internet surveys enable much more control than do paper surveys.

Online surveys will have a cost advantage over telephonic surveys.

Have to keep gazing the net always for its ups and downs in rates.


17. The purpose of experimental research is to study ________ and

__________ relationships.

18. An important characteristic of experimental research is active

manipulation of ________________.

5.8 Web Analytics

It is the objective tracking, collection, measurement, reporting, and analysis

of quantitative internet data to optimise websites and web marketing

initiatives.

e-Marketing Unit 5


Web analytics2 is not just a tool used for measuring website traffic, but also

a tool for business research and market research. Web analytic applications

can also help several companies to measure the results of traditional print

advertising campaigns. It helps to estimate how the traffic to the website has

been changed after the launch of a new advertising campaign. Web

analytics provide data on the number of visitors, page views, etc to gauge

the traffic and popularity trends which help in marketing research.

There are two categories of web analytics: off-site and on-site web analytics.

Off-site web analytics refers to web measurement and analysis irrespective

of whether you own or maintain a website. It includes the measurement of a

website‟s potential audience or opportunity, share of voice or visibility, and

buss or comments that are happening on the Internet.

On-site web analytics measure a visitor's journey on the website. This

includes its drivers and conversions. On-site web analytics measures the

performance of the website in a commercial context. This data is typically

compared with key performance indicators for performance and used to

improve a web site or the response of the audience to a marketing

campaign.

5.8.1 Web Server Log File Analysis

Web servers record some of their transactions in a log file. It was

recognised that these log files could be read by a program to provide data

on the popularity of the website. This gave rise to the web log analysis

software.

In the early 1990s, web site statistics consisted mainly of counting the

number of client requests made to the web server. Initially, each web site

often consisted of a single HTML file. However, in HTML and web sites

images that spanned multiple HTML files were introduced, and hence this

count became less useful. The first proper commercial Log Analyser was

released by IPRO in 1994.

Two units of measure were introduced in the mid 1990s to measure more

accurately the total human activity on web servers. These were page views

and visits. A page view is a request to the web server for a page as to

2 e-marketing by Judy Strauss and Raymond Frost.

e-Marketing Unit 5


oppose a graphic. A visit is an order of requests from a uniquely identified

client that expired after a certain amount of inactivity, usually 30 minutes.

The page views and visits are still commonly displayed metrics. The

emergence of search engine spiders and robots in the late 1990s, along

with web proxies and dynamically assigned IP addresses for large

companies and Internet server providers, made it more difficult to identify

unique human visitors to a website. Log analysers responded by tracking

visits by cookies, and by ignoring requests from known spiders.

5.8.2 Page Tagging

Page tagging takes care of the accuracy of log file analysis in the presence

of caching. And the desire to be able to perform web analytics as an

outsourced service, led to the second data collection method, page tagging

or 'Web bugs'.

In early 1990s, Web counters were commonly seen. These were images

included in a web page that showed the number of times the image had

been requested, which was an estimation of the number of visits to that

page. In the late 1990s, this concept evolved to include a small invisible

image instead of a visible by using JavaScript, to pass along with the image

requesting certain information about the page and the visitor. This

information can then be processed remotely by a web analytics company

and extensive statistics generated.

The web analytics service manages the process of assigning a cookie to the

user, which helps in uniquely identifying the user during their first and

subsequent visits. Acceptance rates of cookies vary significantly between

web sites and may affect the quality of data gathered and reported.

Gathering web site data using a third party data collection server requires an

additional Domain Name system look up by the user's computer to

determine the IP address of the collection server. Occasionally, delays in

completing successful or failed DNS look-ups may result in data not being

collected.


19. ________ is used as a tool for business research and market research.

20. Page tagging is also known as ______________.

21. Page tagging tests the accuracy of _____________.

e-Marketing Unit 5


5.9 Knowledge Management Metrics

Marketing research is not cheap. Marketers often weigh the cost of getting

additional information against the value of potential opportunities or the risk

of possible errors from decisions made with incomplete information. They

are also concerned about the storage cost of all those terabytes of data

coming from Web site logs, online surveys, Web registrations, and other

real-time and real-space approaches. The good news is that data storage

costs have declined steadily since 1998. Two metrics are currently in

widespread use:

ROI: Companies want to know why they should save all those data, how will

they be used, and will the benefits in additional revenues or lowered costs

return an acceptable rate on the storage space investment? For hardware

storage space, ROI usually means total cost savings divided by total cost of

the installation (Gruener, 2001). Notably, companies use ROI to justify the

value of other knowledge management systems as well.

Total Cost of Ownership (TCO): Generally a metric used by information

technology managers, TCO includes not only the cost of hardware,

software, and labour for data storage, but also other items such as cost

savings by reducing Web server downtime and labour requirements. For

example, Galileo International offers travel reservations and maintains 102

terabytes of data – schedule, fare and reservation information for 500

airlines, 47,000 hotels and 37 car rental companies (Radding, 2001) .The

Company booked 345 million reservations in 2000, sometimes handling

10,000 requests a second! Galileo‟s ROI is simple: according to its owner,

Frank Auer, every bit of the firm‟s $1.6 billion in revenue is a return on its

data storage system.

In another example, trucking company Schneider National had enough data

to fill ten 53-foot trailers with floppy disks. But it still could not easily figure

out why it cost $0.20 a pound to deliver cars to a Ford Dealership in Texas

and only $0.17 elsewhere. The firm spent an estimated $2 million to

purchase business intelligence software that allowed employees to get quick

answers to marketing problems and realised a $2.5 million return on that

investment within two years (25 %) (Brown, 2002).

e-Marketing Unit 5



22. ROI is an example _____________________________.

23. ____________________________ is the technique largely used by

Information Technology Managers.

Activity 2

Assuming that you are starting an online marketing channel for electronic

razors, chart out an e-marketing strategy. Your strategy should include all

the details like the promotional channel, audience, type of tools to be

used for data mining, web analytics and so on.

5.10 Summary

Let us recap what we studied in this unit.

E-Marketers need data to take decisions about creating and changing

marketing strategies. This data is collected from a number of sources,

filtered into databases and turned into marketing knowledge that is then

used to develop marketing strategies.

Knowledge management is the process of managing the creation, use, and

dissemination of knowledge.

The different types of data studied are user entry type or profile type, web

document and web Meta data and finally the server and cookie data.

A Marketing Information System (MIS) is the process by which marketers

manage knowledge, by using a system of assessing information needs,

gathering information, analysing it and disseminating it to decision makers.

Data warehouses are repositories for the organisation‟s historical data. Data

from all customer touch points are stored in the warehouse.

Data mining extracts hidden predictive information from the warehouse via

statistical analysis.

5.11 Glossary

Term Description

Caching Storing of web files for later re-use to facilitate quick access by the end user.

Strategy A plan of action designed to achieve a particular goal.

Algorithm Step by step procedure.

e-Marketing Unit 5


5.12 Terminal Questions

1. Write short notes on user entry data and cookie data.

2. Why is knowledge management necessary?

3. What is a Marketing Information System? Explain its importance.

4. Discuss marketing intelligence systems and data based systems.

5. What do you understand by online experimental research and online

survey processes?

6. Briefly describe web analysis.

7. What is knowledge management metrics and how important is it to an

organisation?

5.13 Answers

Self Assessment Questions:

1. Data.

2. Web documents.

3. Cookies

4. Server log and cookie log.

5. Knowledge management.

6. Goal.

7. Planning quicker.

8. c. Manipulating data

9. Data warehouse

10. Decision making.

11. Marketing intelligence.

12. External networking.

13. Online customer feedback systems

14. Training and motivating.

15. True

16. Data mining

17. Cause and Effect

18. Independent variable

19. Web analysis

20. Web bugs

e-Marketing Unit 5


21. Log files analysis

22. Knowledge management metrics

23. Total cost ownership (TCO)

Terminal Questions:

1. Refer section 5.2, Types of data in e-marketing

2. Refer section 5.3, Knowledge management for e-marketing

3. Refer sections 5.4, Marketing Information Systems for e-marketing

4. Refer section 5.5 and 5.6, Marketing Intelligence systems & Managing

database systems

5. Refer sections 5.7, Online experimental research and survey

6. Refer section 5.8, Web analytics

7. Refer section 5.9, Knowledge Management Metrics

5.14 Case-let

Invention and Knowledge

Mr. James invented the photocopy machine in 1934. He tried to sell his in

invention to MNC companies, but his efforts failed as the companies did

not believe that there was a major market for photocopiers. It was left to

the small Italy based company called Tyco to finally market a product that

later became vital for making multiple copies of documents. Modi crop

officially came into existence after which Tyco changed its name replicate

its core business. After decades the company diversified into a number of

businesses, some of those added values to its business model and others

which had to be liquidated.

In the mid of the year 1990‟s the company switched on itself as the

„Document Company‟, to reflect more on its core business. The

knowledge management movement of 1990s encouraged the company to

concentrate more on knowledge sharing initiatives. It started “Spec” which

captured the hints shared informally by the company‟s service

representatives and created a data base of hints that could be accessed

by councils all over the world.

Both internal and commercial also followed and Modi Corp was

recognised as one of the most admired knowledge Enterprise.

e-Marketing Unit 5


Discussion Questions:

1. Why Mr. James failed in selling his invention?

2. What prompted the company to concentrate on knowledge sharing

initiatives? Do you think today it is easier to share knowledge and

information that help e-marketing as well?

This is adapted from the real life scenario on Chester Carlson‟s invention

of the photocopying machine.

References

Strauss Judy, Frost Raymond, E-marketing 2002 – 2nd edition, Free

Press

E-References

www.whatyouveheard.com/2010/07/global-data-warehouse-software-

market-in-retail-industry-2008-2012/

www.en.wikipedia.org/wiki/Web_analytics